Characterization of bio-dynamic speckles through classical and fuzzy mathematical morphology tools
In this paper we characterize dynamic speckle signals, obtaining selective information through the differentiation of morphological patterns of the temporal history of each pixel, using the morphological granulometric function. This method is applied to the analysis of images of apples and corn seed...
| Autores: | , , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2013 |
| País: | Argentina |
| Recursos: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositório: | CONICET Digital (CONICET) |
| Idioma: | inglês |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/80361 |
| Acesso em linha: | http://hdl.handle.net/11336/80361 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Dynamic Speckle Fuzzy Mathematical Morphology Mathematical Morphology Morphological Granulometric Function https://purl.org/becyt/ford/2.2 https://purl.org/becyt/ford/2 |
| Resumo: | In this paper we characterize dynamic speckle signals, obtaining selective information through the differentiation of morphological patterns of the temporal history of each pixel, using the morphological granulometric function. This method is applied to the analysis of images of apples and corn seeds. Studies on the first ones were focused on the activity on their surface, related to healthy and damaged areas, while for seeds on the viability of the embryo and endosperm. Subsequently, the analysis was repeated using fuzzy mathematical morphology techniques, comparing the results obtained by both methods. |
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